Decentralized hardware-in-the-loop scheme

ABSTRACT

A method tests the configuration of an aggregated DERs system using distributed asset managers in a decentralized hardware-in-the-loop (“HIL”) scheme. The managers contain the model of the asset they are meant to control. The method programs an asset manager with a model of a DERs asset. A plurality of asset managers are connected to a central controller. The plurality of asset managers are also connected to a simplified hardware-in-the-loop platform. The simplified HIL platform is configured to solve a network model, a load model, a non-controllable asset model, and a grid model. The method tests the DERs system control structure by using: (a) the simplified HIL platform to solve the network model, the load model, the non-controllable asset model, and the grid model, and (b) the asset manager to solve the model of the DERs asset, without any simulation between the central controller and the distributed asset managers.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of U.S. patent applicationSer. No. 16/683,148, filed Nov. 13, 2019, which claims priority fromprovisional U.S. patent application No. 62/760,823, filed Nov. 13, 2018,entitled, “DECENTRALIZED HARDWARE-IN-THE-LOOP SCHEME,” and naming JorgeElizondo Martinez as inventor, the disclosures of which are incorporatedherein, in their entireties, by reference.

FIELD OF THE INVENTION

Illustrative embodiments generally relate to power distribution networksand, more particularly, illustrative embodiments relate to devices forsimulating power distribution across a power network.

BACKGROUND OF THE INVENTION

The electricity grid connects homes, businesses, and other buildings tocentral power sources. This interconnectedness requires centralizedcontrol and planning, where grid vulnerabilities can cascade quicklyacross the network. To mitigate these risks, aggregated distributedenergy resources (“DERs”) systems (“DERs Systems”), such as microgridsare becoming a popular solution. Microgrids include controlled clustersof electricity generation and storage equipment, as well as loads thatprovide a coordinated response to a utility need and can also operatedisconnected from the main grid. This increases the power systemefficiency and reliability.

The US Department of Energy provides a formal definition of a microgridas a group of interconnected assets, including loads and distributedenergy resources, with clearly defined electrical boundaries that actsas a single controllable entity with respect to the grid. A microgridoften has distributed generators (e.g., diesel generators, gas turbines,etc.), batteries, as well as renewable resources like solar panels orwind turbines.

SUMMARY OF VARIOUS EMBODIMENTS

In accordance with one embodiment of the invention, a method tests theconfiguration of an aggregated distributed energy resources system(“DERs system”) using distributed asset managers in a decentralizedhardware-in-the-loop scheme. The asset managers contain the model of theasset they are meant to control. The method programs an asset managerwith a model of a DERs asset. A plurality of distributed asset managersare connected to a central controller. The plurality of distributedasset managers are also connected to a simplified hardware-in-the-loopplatform (“simplified HIL platform”). The simplified HIL platform isconfigured to solve a network model, a load model, a non-controllableasset model, and a grid model. The method tests the DERs system controlstructure by using: (a) the simplified HIL platform to solve the networkmodel, the load model, the non-controllable asset model, and the gridmodel, and (b) the asset manager to solve the model of the DERs asset,without any simulation between the central controller and thedistributed asset managers.

Among other things, the method may calculate the DQ voltages at eachnode on the simplified HIL platform. The DQ voltages may be sent to therespective distributed asset managers. Additionally, the method maycalculate the respective DQ currents at each distributed asset managerusing their own asset model. The DQ currents may be sent to thesimplified HIL platform. The method may also re-calculate the DQvoltages at each node on the simplified HIL platform. The above stepsmay describe a cycle. In some embodiments, the cycle may be repeateduntil steady state conditions are reached.

Some embodiments calculate the AC sinusoidal voltages at each node onthe simplified HIL platform. The method may send the AC sinusoidalvoltages to the respective distributed asset managers. The method mayalso calculate the respective AC sinusoidal currents at each distributedasset manager using their own asset model. The AC sinusoidal currentsmay be sent to the simplified HIL platform. The method may alsore-calculate the three AC sinusoidal voltages at each node on thesimplified HIL platform. The above steps may describe a cycle. In someembodiments, the cycle may be repeated until steady state conditions arereached.

In some embodiments, the method also calculates, in the respectivedistributed asset manager, the terminal voltage using the terminalcurrent as an input for an asset operating in grid forming or mastermode. Additionally, or alternatively, the method may calculate, in therespective distributed asset managers, the voltage and the frequencyusing the current as an input when all the assets are operating in droopcontrol mode, in which the asset managers do not communicate with acentral controller.

In some embodiments, the method may use the central controller toperform the functions of the simplified HIL platform. Additionally, themodel results may be sent via the same communication network that isused to control the DERs system. Illustrative embodiments may evaluatealternative control strategies when the real DERs system is runningwithout disturbing the system operation. For example, real data acquiredand processed by the distributed asset manager may be used toautomatically improve the accuracy of the distributed asset manager'sasset model over time.

In accordance with another embodiment, an asset manager configured tocontrol distribution of power within an aggregated distributed energyresources system (“DERs system”) having a plurality of assets. The assetmanager is configured to solve a given asset model. The asset managerincludes a given asset model configured to model a real asset. The assetmanager also includes an interface configured to receive assetinformation relating to the given asset model. The interface isconfigured to communicate with at least one other asset manager and/or acentral controller in the DERs system. Additionally, the interface isalso configured to communicate with a simplified hardware-in-the-loopplatform (“HIL platform”). The asset manager includes a functiongenerator operatively coupled with the interface. The function generatoris configured to produce a set point using a local cost function withthe data relating to the given asset model. The local cost functionrepresents a portion of a system cost function for the overall DERssystem. The asset manager also has an asset controller operativelycoupled with the function generator and the given asset model. The assetcontroller is configured to solve the given asset model as a function ofthe set point to determine a simulated operating point for the givenasset. The asset controller is further configured to forward theoperating point to the HIL platform via the interface.

In accordance with yet another embodiment, a method uses a simplifiedhardware-in-the-loop scheme. The method provides a simplifiedhardware-in-the-loop computer configured to solve a network model, aload model, a non-controllable asset model, and a grid model of adistributed energy resources system. The method also provides aplurality of asset models to a plurality of asset managers,respectively, and the asset managers are configured to communicate witha central controller and the computer device. Each of the plurality ofasset models is solved using the respective asset manager to produceasset model data. The method also provides the asset model data from theasset manager to the simplified hardware-in-the-loop computer.

Illustrative embodiments of the invention are implemented as a computerprogram product having a computer usable medium with computer readableprogram code thereon. The computer readable code may be read andutilized by a computer system in accordance with conventional processes.

BRIEF DESCRIPTION OF THE DRAWINGS

Those skilled in the art should more fully appreciate advantages ofvarious embodiments of the invention from the following “Description ofIllustrative Embodiments,” discussed with reference to the drawingssummarized immediately below.

FIG. 1 schematically shows a DERs system with a simplifiedhardware-in-the-loop platform in accordance with illustrativeembodiments of the invention.

FIG. 2 schematically shows an asset manager in accordance withillustrative embodiments of the invention.

FIG. 3 schematically shows a DERs system with a simplifiedhardware-in-the-loop platform in accordance with illustrativeembodiments of the invention.

FIG. 4 schematically shows a process of implementing a change in aphysical variable of the DERs system of FIG. 3 .

DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

In illustrative embodiments, a simplified hardware-in-the-loop platformruns a simulation of an electric network model that provides realisticand real-time testing for one or more simulated asset models in anaggregated distributed energy resources system (“DERs system”). Each ofthe asset models has an underlying mathematical representation of thebehavior of a given real asset. Unlike typical HIL platforms, thesimplified HIL platform does not solve the asset models. Instead, thesimplified HIL platform communicates with one or more asset managersthat each solve their respective asset model. Accordingly,decentralizing the solving of the asset models to the asset managersenables a decentralized simplified HL scheme. Details of illustrativeembodiments are discussed below.

FIG. 1 schematically shows a simplified hardware-in-the-loop platform 10(the “HIL platform 10”) working with a DERs system 8 in accordance withillustrative embodiments of the invention. The DERs system 8 includes anelectrical network 12 that connects a plurality of assets. Like otherDERs systems 8, the system 8 may have a central controller 14 thatfacilitates communication between the various assets. Specifically, theassets communicate with the central controller 14 through theirrespective asset manager 16. In illustrative embodiments, each assetmanager 16 also contains an asset model 18 (also referred to as avirtual asset 18) configured to simulate the real asset. Althoughillustrative embodiments may include real assets in addition to assetmodels 18, any reference to “the asset” in the discussion below shouldbe understood to refer to the asset model 18, as opposed to the realasset, unless the context otherwise requires.

FIG. 1 shows a plurality of the asset managers 16 each having thevirtual asset 18. However, it should be understood that illustrativeembodiments may have one or more asset managers 16 connected to thenetwork 12, and each manager 18 may have one or more asset models 18.Furthermore, each asset model 18 may model a different type of asset(e.g., a battery, solar panels, wind turbine, etc.). Although not shown,illustrative embodiments may include one or more real assets connectedto the network 12 in addition to the model 18.

The DERs system also includes the simplified HIL platform 10 thatcontains a network model 30. A typical HIL platform simulates the loadmodels, non-controllable renewable models, network models, and assetmodels, among other things. For example, the central controller of theprior art may contain the HIL platform 10 and solve each of the assetmodels 18 in addition to the other models described previously.

In illustrative embodiments, the simplified HIL platform 10 does notsimulate the assets 18. Instead, the simulation of each assets model 18is performed by the respective asset manager 16. Accordingly, thesimplified HIL platform 10 is enabled by decentralizing the simulationof the various asset models 18. Specifically, in illustrativeembodiments each asset manager 16 contains and solves the model for itsgiven virtual asset 18. It should be noted that while the centralcontroller 14 may be part of the network 12 and may communicate with theasset manager(s) 16, the given asset 18 is simulated on thecorresponding asset manager 16 (e.g., Asset Manager 1 simulates AssetModel 1, Asset Manager 2 simulates Asset Model 2, and Asset Manager 3simulates Asset Model 3). Thus, illustrative embodiments may test theDERs system 8 without any simulation between the central controller 14and the distributed asset managers 16.

Although the simplified HIL platform 10 is shown as being in a differentdevice from the central controller 14 and the asset managers 16, inillustrative embodiments the simplified HIL simulation 10 may be run onthe central controller 14 and/or one or more of the asset managers 16instead of on a separate device (i.e., a computer).

FIG. 2 schematically shows details of one of the asset managers 16 ofFIG. 1 in accordance with illustrative embodiments of the invention. Inillustrative embodiments, the asset manager 16 may be the same orsimilar to the asset manager 16 described in U.S. patent applicationSer. No. 16/054,377, incorporated herein by reference in its entirety.As shown in FIG. 2 , the asset manager 16 of FIG. 2 has a plurality ofcomponents that together perform some of its functions. Each of thesecomponents is operatively connected by any conventional interconnectmechanism. For example, FIG. 2 simply shows a bus communicating witheach of the components. Those skilled in the art should understand thatthis generalized representation can be modified to include otherconventional direct or indirect connections. Accordingly, discussion ofa bus is not intended to limit various embodiments.

The asset manager 16 includes an asset controller 20 that is configuredto, among other things, use a local cost function to manage operation ofthe real asset and/or asset model 18. The asset controller 20 uses thecost function to determine a set point of the real asset and/or virtualasset 18. Each asset model 18 has an independent (asset-level) costfunction that the asset manager 16 maintains. Additionally, someembodiments may include a central controller 14 (external to the assetmanager 16) that dynamically and efficiently updates the system-levelcost function.

Each one of the asset managers 16 calculates the set point of its assetmodel 18. In some embodiments, the set point may be used to calculatehow much current the asset injects into the system 8. However, in someother embodiments, the set point may be used to calculate how much powershould be injected into the system 8. The virtual asset 18 uses the setpoint to change its simulated operation point (also referred to as asimulated output). The operation point is the combination of the realand reactive power that the simulated or real asset 18 is injecting intothe system 8. The operation point may also include all the internalstates of the simulated or real asset 18, such as temperatures, storedenergy, voltages, etc.

The asset manager 16 includes a memory 22 for storing asset data, aninterface 24 to communicate with the asset 18 and other devices, afunction generator 26 configured to produce the local cost function, andthe asset model 18 used to emulate the behavior of the asset, such asdiesel generators, gas turbines, batteries, solar panels, wind turbines,loads, etc. Although the interface 24 may communicate with the asset 18using a protocol that may be proprietary to its assigned asset, itpreferably communicates with the central controller 14 and/or otherasset managers 16 and/or the simplified HIL platform 10 using acommunication protocol for DERs systems 8 known to those of skill in theart. Each of these components and other components cooperate to performthe various discussed functions.

In addition to the components described herein, the asset manager 16 mayinclude other modules, such as a voltmeter, topography engine, physicalcharacteristic analysis engine, or others, as described in U.S.application Ser. Nos. 16/054,377 and 16/054,967, both of which areincorporated herein by reference in their entireties.

Indeed, it should be noted that FIG. 2 only schematically shows each ofthese components. Those skilled in the art should understand that eachof these components can be implemented in a variety of conventionalmanners, such as by using hardware, software, or a combination ofhardware and software, across one or more other functional components.For example, the controller 20 may be implemented using a plurality ofmicroprocessors executing firmware. As another example, the controller20 may be implemented using one or more application specific integratedcircuits (i.e., “ASICs”) and related software, or a combination ofASICs, discrete electronic components (e.g., transistors), andmicroprocessors. Accordingly, the representation of the controller 20and other components in a single box of FIG. 2 is for simplicitypurposes only. In fact, in some embodiments, the controller 20 of FIG. 2is distributed across a plurality of different machines—not necessarilywithin the same housing or chassis.

It should be reiterated that the representation of FIG. 2 is asignificantly simplified representation of an actual asset manager 16.Those skilled in the art should understand that such a device may havemany other physical and functional components, such as centralprocessing units, communication modules, protocol translators, sensors,meters, etc. Accordingly, this discussion is in no way intended tosuggest that FIG. 2 represents all the elements of an asset manager.

FIG. 3 schematically shows the DERs system 8 with the simplified HILplatform 10 in accordance with illustrative embodiments. As previouslydescribed, the DERs system 8 has a plurality of the asset managers 16each having a virtual asset model 18. As shown, the DERs system 8 inthis example has three controllable virtual assets 18 (i.e., a batterysystem, a diesel generator, and a controllable load). Notably,illustrative embodiments use a decentralized control structure (i.e.,each virtual asset 18 is equipped with its own distributed asset manager16 used to model the respective virtual asset 18).

Although a plurality of asset managers 16 are shown, it should beunderstood that illustrative embodiments may operate with only a singleasset manager 16. Additionally, although not shown, illustrativeembodiments may include one or more asset manager 16 that controls areal asset (in addition to or instead of a virtual asset 18). Indeed, inillustrative embodiments, after the asset model 18 is tested, the assetmanager 16 may be coupled with the real asset that was simulated by theasset model 18. In some embodiments, the asset manager 16 may be coupledwith a real asset and include the asset model 18. For example, the realasset may be turned off to determine the adequacy of replacing the realasset with another real asset represented by the model 18.

FIG. 4 shows a process 400 of using the DERs system 8 with thesimplified HIL platform 10 of FIG. 3 . It should be noted that thisprocess can be a simplified version of a more complex process of usingthe simplified HIL platform. As such, the process may have additionalsteps that are not discussed. In addition, some steps may be optional,performed in a different order, or in parallel with each other.Accordingly, discussion of this process is illustrative and not intendedto limit various embodiments of the invention. Although this process isdiscussed with regard to asset models 18, the process of FIG. 2 can beexpanded to cover processes including real assets at the same time.Thus, it should be understood that illustrative embodiments are notlimited to operating with DERs systems 8 having the configuration shownin FIG. 3 .

The process 400 of FIG. 4 shows the distributed asset managers 16solving the virtual asset model 18 to match the central controlcommands, and the simplified HIL platform 10 solving for the terminalvoltages of the virtual assets.

The process 400 begins at step 402, which adjusts the price signal p ofthe system-level cost function. The price signal p (or “price”) is asignal that generally increases in value when there is more demand thansupply of energy, and generally decreases when there is more supply thandemand of energy. For the purposes of this discussion, assume that thesystem 8 is in a steady state or period steady state. However, it shouldbe understood that the system 8 does not have to be in steady state inuse, and that discussion thereof is intended to facilitate ease ofdiscussion rather than to limit illustrative embodiments of theinvention.

Accordingly, the price signal p may change when the central controller14 requests additional power from the system 8. For example, the centralcontroller 14 may request that power output of the system 8 increasefrom 3 kW to 6 Kw. Because there are three assets 18 in FIG. 3 (i.e.,the assets managed by asset manager 1, asset manager 2, and assetmanager 3, respectively) the system 8 may respond in different waysbased on the optimizing the cost function. For example, the costfunction may be used to determine that it is best to inject 2 kW fromeach asset. Alternatively, the cost function may be used to determinethat 4 kW from asset 1 and 1 kW each from asset 2 and asset 3 isoptimal. Accordingly, the change in power demands causes a change anadjustment in the price of the system-level cost function.

At step 404, the asset manager 16 receives the price and calculates aset point for the asset model 18. The set point instructs the asset 18as to how much power and/or current to inject into the system 8. FIG. 3shows the central controller 14 sending the new price, but in otherembodiments the price 1 may be sent by another of the distributed assetmanagers 16 or defined by a change in its terminal frequency or voltage(for example in a droop control implementation). The asset managers 16receive the price and use their local cost function to calculate the setpoint for the asset 18. Thus, illustrative embodiments use local costfunctions in the asset managers 17 to minimize the cost function of theoverall system.

At step 406, the asset manager 16 simulates the output of the asset 18by solving the model using the set point (e.g., Asset Model 1 solves forthe battery system). By solving the model, the system 8 determines theoperation point of the asset (i.e., how the model expects the asset 18to respond to the set point). In illustrative embodiments, the assetmodel 18 may have the form of a differential equation as shown in FIG. 3, where x ₁ is a vector with the state variables that represent thedynamics of the battery-inverter system (ex. DC voltage, temperature,etc.), v ₁ is a vector containing the terminal voltage to the asset,P_(sp) is a scalar containing the real power set-point, and Q_(sp) is ascalar of the reactive power set-point.

It should be understood that while the set point represents a desiredvalue for real and reactive power that the simulated or real assetinject into the system, the operation point represents the combinationof the actual real and reactive power that the simulated or real assetis injecting into the system. Furthermore, the operation point may alsoinclude all the internal states of the DER, such as temperature, storedenergy, voltages, etc. The simulated operation point is a physicalvariable (e.g., in this case it is current). For example, the modeloperation point is represented by 1, a vector containing the terminalcurrents going into the simplified HIL platform 10 that contains theelectrical system 12 model. The operation point of the asset model 18(e.g., the current that the battery injects to grid) is used at step410.

At step 408, the simulated operation point is sent to the simplified HILplatform 10, for example, using the interface 24. The new outputcurrents from the asset 18 (e.g., battery system 18) are sent to thesimplified HIL platform 10. The method to send the operation point cantake many forms. For example, analog signals and/or a communicationprotocol may be used to send the operation point to the simplified HILplatform 10.

At step 410, the simplified HIL platform 10 receives the simulatedoperation point (e.g., the new currents 3 shown in FIG. 3 ) from theasset model 18 (e.g., the battery system) and solves power flows in thenetwork due to the simulated currents and the uncontrollable assetmodels 30. The model may take a differential-algebraic equation 4(“DAE”) form as shown in FIG. 3 , although different models may be usedin alternative embodiments. In the equations, x _(m) represent the statevariables of the partial DERs system model, i={ī₁, ī₂, ī₃} is thecollection of the currents from the three controllable assets 18, andthe output of the model is v={v ₁, v ₂, v ₃}, which is the collection ofvoltages at the terminals of the three controllable assets 18. Thealgebraic equation (i.e., the second line in the DAE 4 in FIG. 3 )arises from Kirchhoff current law in the network.

By solving the electrical network model 30, illustrative embodimentscalculate the voltage each asset 18 sees in its terminal, and/or thetotal combined power output of all the assets 18. Accordingly, at step412, the new calculated voltages v ₁, v ₂, and v ₃ are sent to thedistributed asset managers 16.

As shown in FIG. 4 , after the voltages are sent to the asset managers16, the distributed asset managers 16 may use the new voltages togenerate new operation points (e.g., currents) at step 406, and thensend those new currents to the simplified HIL platform at step 408. Theprocess may then proceed to step 410, where the simplified HIL platform10 may recalculate the voltages. The process may be repeated until asteady state conditions are reached. When steady state conditions arereached, the process comes to an end. Alternatively, the process maycome to an end upon user decision (e.g., in the case where the process400 continues to loop because the system is unstable).

It should be understood that illustrative embodiments include variationson the process 400 described above. For example, one of the assets mayoperate in Grid Forming or Master mode. Accordingly, the asset's modeloutput is the terminal voltage instead of the terminal current. In thatembodiment, the currents are inputs to the model. As yet anotherexample, when all the assets are operating in droop control mode, thereis no central controller. Thus, all the assets have models where theoutputs are the voltage and frequency and the currents the inputs.Accordingly, it should be understood that illustrative embodiments areintended to cover a variety of embodiments and are not limited to thedisclosed embodiment described with reference to FIG. 3 .

In another embodiment, the central controller 14 may act as thesimplified HIL platform 10 itself, and the model results may be sent viathe same communication network that is used to control the DERs system.

It should be apparent that the above-described decentralized HIL schemeenables the simplified HIL platform 10 and provides a number ofadvantages. For example, illustrative embodiments allow the use ofparallel computing. In some embodiments, the computation is distributedamong a plurality of processing devices (e.g., asset managers 16) thatare connected as they would otherwise be in non-simulation settings,allowing faster and more accurate solving of the asset model 18. As afurther advantage, the simplified HIL platform 10 enables an easilytestable modular DERs system 8. For example, adding and removing adistributed asset manager 16 automatically adds or removes thecorresponding virtual asset 18 from the DERs system 8; there is no needto make any changes to the HIL platform 10.

Additional benefits provided by illustrative embodiments includeimproved model accuracy. In some embodiments, since each asset ismodeled independently in its respective distributed asset manager 16,the model 18 may be more accurate, as real data can be used to improvethe asset model 18 over time. Furthermore, the simplified HIL platform10 may be implemented in the field after the distributed asset managers16 have already been put in place. As an additional benefit, the HILplatform 10 may be used even when the real system 8 is running (e.g., totest alternative control strategies, without disturbing the system 8operation). Data may also be collected to refine the asset model(s) 18.Additional advantages include that the signals between the distributedasset managers 16 and the simplified HIL platform 10 may be physicalvariables (e.g., voltages, currents, etc.) instead of control commands.Accordingly, illustrative embodiments make implementation easier todebug and understand.

The communication signals between the distributed asset managers 16 andthe HIL platform 10 can be adapted to change the level of detail desiredin the implementation. For example, in some embodiments, the simplifiedHIL platform 10 calculates the DQ voltages at each node and sends themto the distributed asset managers 16. The DQ voltages are the valuesobtained from applying the direct-quadrature-zero transformation to thesinusoidal voltages at the terminals of the asset 18. The transformationchanges the values from a static reference frame, to a reference framethat is rotating at the same frequency as the sinusoids. The distributedasset managers 16 may then use their own asset model 18 to calculate andsend the DQ currents to the simplified HIL platform 10. Additionally, oralternatively, the simplified HIL platform 10 may calculate the three ACsinusoidal voltages and send the calculation to the distributed assetmanagers 16, which then solve their respective asset models 18 tocalculate and send the three AC sinusoidal currents back.

Various embodiments of the invention may be implemented at least in partin any conventional computer programming language. For example, someembodiments may be implemented in a procedural programming language(e.g., “C”), or in an object oriented programming language (e.g.,“C++”). Other embodiments of the invention may be implemented aspreprogrammed hardware elements (e.g., application specific integratedcircuits, FPGAs, and digital signal processors), or other relatedcomponents.

In an alternative embodiment, the disclosed apparatus and methods (e.g.,see the various flow charts described above) may be implemented as acomputer program product for use with a computer system. Suchimplementation may include a series of computer instructions fixedeither on a tangible, non-transitory medium, such as a computer readablemedium (e.g., a diskette, CD-ROM, ROM, or fixed disk). The series ofcomputer instructions can embody all or part of the functionalitypreviously described herein with respect to the system.

Those skilled in the art should appreciate that such computerinstructions can be written in a number of programming languages for usewith many computer architectures or operating systems. Furthermore, suchinstructions may be stored in any memory device, such as semiconductor,magnetic, optical or other memory devices, and may be transmitted usingany communications technology, such as optical, infrared, microwave, orother transmission technologies.

Among other ways, such a computer program product may be distributed asa removable medium with accompanying printed or electronic documentation(e.g., shrink wrapped software), preloaded with a computer system (e.g.,on system ROM or fixed disk), or distributed from a server or electronicbulletin board over the network (e.g., the Internet or World Wide Web).In fact, some embodiments may be implemented in a software-as-a-servicemodel (“SAAS”) or cloud computing model. Of course, some embodiments ofthe invention may be implemented as a combination of both software(e.g., a computer program product) and hardware. Still other embodimentsof the invention are implemented as entirely hardware, or entirelysoftware.

Disclosed embodiments, or portions thereof, may be combined in ways notlisted above and/or not explicitly claimed. In addition, embodimentsdisclosed herein may be suitably practiced, absent any element that isnot specifically disclosed herein. Accordingly, the invention should notbe viewed as being limited to the disclosed embodiments.

The embodiments of the invention described above are intended to bemerely exemplary; numerous variations and modifications will be apparentto those skilled in the art. Such variations and modifications areintended to be within the scope of the present invention as defined byany of the appended claims.

What is claimed is:
 1. A method of testing the configuration of anaggregated distributed energy resources system (“DERs system”) usingdistributed asset managers containing the model of the asset they aremeant to control in a decentralized hardware-in-the-loop scheme, themethod comprising: programming an asset manager with a model of a DERsasset; connecting a plurality of distributed asset managers to a centralcontroller, connecting the plurality of distributed asset managers to asimplified hardware-in-the-loop platform (“simplified HIL platform”)configured to solve a network model, a load model, a non-controllableasset model, and a grid model; testing the DERs system control structureby using: (a) the simplified HIL platform to solve the network model,the load model, the non-controllable asset model, and the grid model,and (b) the asset manager to solve the model of the DERs asset; defininga cycle that includes: calculating the DQ (direct-quadrature-zerotransformation) voltages at each node on the simplified HIL platform;sending the DQ voltages to the respective distributed asset managers;calculating the respective DQ currents at each distributed asset managerusing their own asset model; sending the DQ currents to the simplifiedHIL platform; re-calculating the DQ voltages at each node on thesimplified HIL platform; and repeating the cycle until steady stateconditions are reached.
 2. The method of testing the configuration of aDERs system of claim 1, further comprising: defining a cycle thatincludes: calculating the AC sinusoidal voltages at each node on thesimplified HIL platform; sending the AC sinusoidal voltages to therespective distributed asset managers; calculating the respective ACsinusoidal currents at each distributed asset manager using their ownasset model; sending AC sinusoidal currents to the simplified HILplatform; re-calculating the three AC sinusoidal voltages at each nodeon the simplified HIL platform; and repeating the cycle until steadystate conditions are reached.
 3. The method of testing the configurationof a DERs system of claim 1, further comprising: calculating, in therespective distributed asset manager, the terminal voltage using theterminal current as an input for an asset operating in grid forming ormaster mode.
 4. The method of testing the configuration of a DERs systemof claim 1, further comprising: calculating, in the respectivedistributed asset managers, the voltage and the frequency using thecurrent as an input when all the assets are operating in droop controlmode, in which the asset managers do not communicate with a centralcontroller.
 5. The method of testing the configuration of a DERs systemof claim 1, further comprising: using the central controller to performthe functions of the simplified HIL platform; and sending the modelresults via the same communication network that is used to control theDERs system.
 6. The method of testing the configuration of a DERs systemof claim 1, further comprising: evaluating alternative controlstrategies when the real DERs system is running without disturbing thesystem operation.
 7. The method of testing the configuration of a DERssystem of claim 1, further comprising: using real data acquired andprocessed by the distributed asset manager to automatically improve theaccuracy of the distributed asset manager's asset model over time. 8.The method of testing the configuration of a DERs system of claim 1,further comprising: programming each of a plurality of distributed assetmanagers with a respective model of a DERs asset.
 9. A computer programproduct for use on a computer system for distributing power from anaggregated distributed energy resources system (“DERs system”) having aplurality of assets, the computer program product comprising a tangible,non-transient computer usable medium having computer readable programcode thereon, the computer readable program code comprising: programcode for communicating with a plurality of asset managers to manageassets including a real asset and an asset model, the assets each havinga local dedicated asset manager separate from the other asset manager,each asset manager having an interface; program code for producing, foreach asset, a local cost function using its local dedicated assetmanager, each local dedicated asset manager producing its local costfunction using data relating to its local asset, the cost functions ofthe plurality of assets in the DERs system together representing asystem grid cost function for the overall DERs system; program code fordetermining, using the local cost function as part of the system costfunction, a set point for the asset model; program code for causing theasset manager to solve the asset model using the setpoint, whereinsolving the asset model produces an operation point for the asset model;program code for communicating the operation point for the asset modelto a simplified hardware-in-the-loop platform; program code for testingthe DERs system using the simplified hardware-in-the-loop platform;program code for calculating the DQ (direct-quadrature-zerotransformation) voltages at each node on the simplified HIL platform;program code for sending the DQ voltages to the respective distributedasset managers; program code for calculating the respective DQ currentsat each distributed asset manager using their own asset model; andprogram code for sending the DQ currents to the simplified HIL platform;and program code for re-calculating the DQ voltages at each node on thesimplified HIL platform.
 10. The computer program product of claim 9,further comprising: program code for calculating the AC sinusoidalvoltages at each node on the simplified HIL platform; program code forsending the AC sinusoidal voltages to the respective distributed assetmanagers; program code for calculating the respective AC sinusoidalcurrents at each distributed asset manager using their own asset model;program code for sending AC sinusoidal currents to the simplified HILplatform; and program code for re-calculating the three AC sinusoidalvoltages at each node on the simplified HIL platform.
 11. The computerprogram product of claim 9, further comprising: program code forcalculating, in the respective distributed asset manager, the terminalvoltage using the terminal current as an input for an asset operating ingrid forming or master mode.
 12. The computer program product of claim9, further comprising: program code for calculating, in the respectivedistributed asset managers, the voltage and the frequency using thecurrent as an input when all the assets are operating in droop controlmode, wherein the asset managers do not communicate with a centralcontroller.
 13. The computer program product of claim 9, wherein themodel results are sent via the same communication network that is usedto control the DERs system.
 14. The computer program product of claim 9,further comprising: program code for testing the simulated DERs systemwhile the real DERs system is running without disturbing the operationof the real DERs system.